Quasi-rectangular shield tunneling is a cutting-edge trenchless method for constructing metro tunnels with double tubes, owing to its advantages in saving underground space and reducing ground disturbance. However, the conventional quasi-rectangular shield tunneling method is not applicable when constructing a tunnel without a center pillar, such as a scissor crossover section of a metro line. Therefore, the 0-θ tunneling method, which combines the quasi-rectangular shield and pipe jacking methods, was investigated in this study to solve the aforementioned construction challenges. This study presents a case study of the Sijiqing Station of the Hangzhou Metro Line 9 in China, in which the 0-θ method was first proposed and applied. Key techniques such as switching between two types of tunneling modes and the tunneling process control in complex construction environments were investigated. The results demonstrated that the 0-θ method can address the technical challenges presented by the post-transition line with a high curvature and a scissors crossover line. In addition, the adoption of the 0-θ method ensured that the transformation between shield tunneling and pipe jacking was safe and efficient. The ground settlement monitoring results demonstrated that the disturbance to the surrounding environment can be limited to a safe level. This case study contributes to the construction technology for a metro tunnel containing both post-transition lines with a small turning radius and a scissors crossover line. A practical construction experience and theoretical guidance were provided in this study, which are of significance for both the industry and academia.

Post-tensioning self-centering walls are a well-developed and resilient technology. However, despite extensive research, the application of this technology has previously been limited to low-rise buildings. A ten-story self-centering wall building has now been designed and constructed using the state-of-art design methodologies and construction detailing, as described in this paper. The building is designed in accordance with direct displacement-based design methodology, with modification of seismic demand due to relevant issues including higher-mode effects, second order effects, torsional effects, and flexural deformation of wall panels. Wall sections are designed with external energy-dissipating devices of steel dampers, and seismic performance of such designed self-centering walls is evaluated through numerical simulation. It is the first engineering project that uses self-centering walls in a high-rise building. The seismic design procedure of such a high-rise building, using self-centering wall structures, is comprehensively reviewed in this work, and additional proposals are put forward. Description of construction detailing, including slotted beams, flexible wall-to-floor connections, embedded beams, and damper installation, is provided. The demonstration project promotes the concept of seismic resilient structures and contributes to the most appealing city planning strategy of resilient cities at present. The paper could be a reference for industry engineers to promote the self-centering wall systems worldwide.

Cement-based materials are brittle and crack easily under natural conditions. Cracks can reduce service life because the transport of harmful substances can cause corrosion damage to the structures. This review discusses the feasibility of using microbial self-healing agents for crack healing. Tubular and spherical carriers can be used to load microbial self-healing agents and protect microbes, which prolongs the self-healing time. The area self-healing ratio, permeability, mechanical strength, precipitation depth method, numerical modeling, and ultrasonic method can be employed to identify the self-healing effect of cracks. Moreover, the self-healing mechanism is systematically analyzed. The results showed that microbial self-healing agents can repair cracks in cement-based materials in underground projects and dam gates. The difficulties and future development of self-healing cracks were analyzed. A microbial self-healing agent was embedded in the cement-based material, which automatically repaired the developing cracks. With the development of intelligent building materials, self-healing cracks have become the focus of attention.

Deep excavations in dense urban areas have caused damage to nearby existing structures in numerous past construction cases. Proper assessment is crucial in the initial design stages. This study develops equations to predict the existing pile bending moment and deflection produced by adjacent braced excavations. Influential parameters (i.e., the excavation geometry, diaphragm wall thickness, pile geometry, strength and small-strain stiffness of the soil, and soft clay thickness) were considered and employed in the developed equations. It is practically unfeasible to obtain measurement data; hence, artificial data for the bending moment and deflection of existing piles were produced from well-calibrated numerical analyses of hypothetical cases, using the three-dimensional finite element method. The developed equations were established through a multiple linear regression analysis of the artificial data, using the transformation technique. In addition, the three-dimensional nature of the excavation work was characterized by considering the excavation corner effect, using the plane strain ratio parameter. The estimation results of the developed equations can provide satisfactory pile bending moment and deflection data and are more accurate than those found in previous studies.

Three-dimensional concrete printing (3DCP) is increasingly being applied in harsh environments and isolated regions. However, the effective utilization of aeolian sand (AS) resources and by-products derived from arid zones for 3DCP is yet to be fully realized. This study developed a three-dimensional (3D) printing composite using AS and magnesium oxychloride cement (MOC) from local materials. The effects of the mole ratio of MgO/MgCl₂ and sand/binder (S/B) ratio on the mechanical properties such as water resistance, drying shrinkage strain, rheology, and printability, were investigated systematically. The results indicated that the optimal mole ratio of MgO/MgCl₂ was 8, which yielded the desired mechanical performance and water resistance. Furthermore, the S/B ratio can be increased to three within the desired printability to increase the AS utilization rate. The rheological recovery and buildability of the 3D-printed MOC with AS were verified. These findings provide a promising strategy for construction in remote deserts.

With the development of self-healing technology, the overall properties of the microcapsule-enabled self-healing concrete have taken a giant leap. In this research, a detailed assessment of current research on the microcapsule-enabled self-healing concrete is conducted, together with bibliometric analysis. In the bibliometric analysis, various indicators are considered. The current state of progress regarding self-healing concrete is assessed, and an analysis of the temporal distribution of documents, organizations and countries of literature is conducted. Later, a discussion of the citations is analyzed. The research summarizes the improvements of microcapsule-enabled self-healing cementitious composites and provides a concise background overview.

Three-dimensional concrete printing (3DCP) can proliferate the industrialization of the construction sector, which is notoriously conservative and indolent toward changes. However, the mechanical behavior of 3DCP should be characterized and modeled considering the interfaces when its performance is thoroughly compared to that of the existing concrete construction methods. This study presents an experimental and numerical investigation of uniaxial compression and three-point bending (TPB) tests on extruded 3DCP beams in different loading directions. The orientation of translational and depositional interfaces with respect to the direction of loading influenced the strength. Both the elastic and post-damage behavior of the 3DCP specimens were compared with those of the conventionally cast specimen under quasi-static loading conditions. Despite the higher compressive strength of the casted specimen, the flexural strength of the 3DCP specimens was higher. This study employed the finite element and cohesive zone models of the appropriate calibrated traction-separation law to model fracture in the notched TPB specimens. Furthermore, the real-time acoustic emission test revealed the nature of failure phenomenon of three-dimensional-printed specimens under flexion, and accordingly, the cohesive law was chosen. The predicted load−displacement responses are in good agreement with the experimental results. Finally, the effects of cohesive thickness and notch shape on the performance under bending were explored through parametric studies.

Balance of the groundwater and ecology is crucial for controlled discharge. However, regarding the segments of tunnel boring machines (TBMs) under high water pressure, the stability of the lining structure is often reduced by excessive drain holes required to achieve this balance. The large discharge of pinholes can easily have severe consequences, such as the lowering of the groundwater table, drying of springs, and vegetation wilting. Thus, in this study, according to the fluid–structure coupling theory, a new drainage design for TBM segments was developed by considering a mountain tunnel subject to a high water pressure as a case study. The evolution characteristics, including the external water pressure of the lining, discharge volume of the segment, and groundwater-table drawdown, were investigated via numerical modeling with drain holes and pinholes. The results indicated that the optimal design parameters of drainage segments for the project case were as follows: a circumferential spacing angle and longitudinal number on one side of a single ring of 51° and 2, respectively, for the drain holes and an inclination angle and length of 46.41° and 0.25 times the grouting thickness, respectively, for the pin holes.

A novel approach based on the upper bound theory is proposed to assess the stability of excavated slopes with spatially variable clay in undrained conditions. The proposed random limit analysis is a combination of the deterministic slope stability limit analysis together with random field theory and Monte Carlo simulation. A series of analyses is conducted to verify the potential application of the proposed method and to investigate the effects of the soil undrained shear strength gradient and the spatial correlation length on slope stability. Three groups of potential sliding surfaces are identified and the occurrence probability of each sort of failure mechanism is quantified for various slope ratios. The proposed method is found to be feasible for evaluating slope reliability. The obtained results are helpful in understanding the slope failure mechanism from a quantitative point of view. The paper could provide guidance for slope targeted local reinforcement.

Three-dimensional printable concrete requires further development owing to the challenges encountered, including its brittle behavior, high cement requirement for the buildability of layers, and anisotropic behavior in different directions. The aim of this study is to overcome these challenges. First, three-dimensional printable concrete mixtures were prepared using silica fume, ground blast furnace slag, and metakaolin, instead of cement, to reduce the amount of cement. Subsequently, the rheological and mechanical behaviors of these concretes were investigated. Second, three-dimensional printable concrete mixtures were prepared using 6-mm-long steel and synthetic fibers to eliminate brittleness and determine the effect of those fibers on the anisotropic behavior of the concrete. As a result of this study, it is understood that printable concretes with extremely low permeability and high buildability can be achieved using mineral additives. In addition, results showed that three-dimensional concrete samples containing short steel fibers achieve fracture energies up to 36 times greater than that of plain concrete. Meanwhile, its characteristic length values, as indicators of ductility, are 22 times higher than those of plain concrete. The weakest strength was recorded at the interfaces between layers. The bending and splitting tensile strengths of three-dimensional printed plain concrete samples were 15% and 19% lower than those of casted samples, respectively. However, the addition of fibers improved the mechanical strength of the interfaces significantly.

Training samples for deep learning networks are typically obtained through various field experiments, which require significant manpower, resource and time consumption. However, it is possible to utilize simulated data to augment the training samples. In this paper, by comparing the actual experimental model with the simulated model generated by the gprMax [1] forward simulation method, the feasibility of obtaining simulated samples through gprMax simulation is validated. Subsequently, the samples generated by gprMax forward simulation are used for training the network to detect objects in existing real samples. At the same time, aiming at the detection and intelligent recognition of road sub-surface defects, the Swin-YOLOX algorithm is introduced, and the excellence of the detection network, which is improved by augmenting the simulated samples with real samples, is further verified. By comparing the prediction performance of the object detection models, it is observed that the model trained with mixed samples achieved a recall of 94.74% and a mean average precision (mAP) of 97.71%, surpassing the model trained only on real samples by 12.95% and 15.64%, respectively. The feasibility and excellence of training the model with mixed samples are confirmed. The potential of using a fusion of simulated and existing real samples instead of repeatedly acquiring new real samples by field experiment is demonstrated by this study, thereby improving detection efficiency, saving resources, and providing a new approach to the problem of multiple interpretations in ground penetrating radar (GPR) data.

The accurate prediction of bearing capacity is crucial in ensuring the structural integrity and safety of pile foundations. This research compares the Deep Neural Networks (DNN), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), and Bidirectional LSTM (BiLSTM) algorithms utilizing a data set of 257 dynamic pile load tests for the first time. Also, this research illustrates the multicollinearity effect on DNN, CNN, RNN, LSTM, and BiLSTM models’ performance and accuracy for the first time. A comprehensive comparative analysis is conducted, employing various statistical performance parameters, rank analysis, and error matrix to evaluate the performance of these models. The performance is further validated using external validation, and visual interpretation is provided using the regression error characteristics (REC) curve and Taylor diagram. Results from the comparative analysis reveal that the DNN (Coefficient of determination (R²)_{training (TR)} = 0.97, root mean squared error (RMSE)_TR = 0.0413; R²_{testing (TS)} = 0.9, RMSE_TS = 0.08) followed by BiLSTM (R²_TR = 0.91, RMSE_TR = 0.782; R²_TS = 0.89, RMSE_TS = 0.0862) model demonstrates the highest performance accuracy. It is noted that the BiLSTM model is better than LSTM because the BiLSTM model, which increases the amount of information for the network, is a sequence processing model made up of two LSTMs, one of which takes the input in a forward manner, and the other in a backward direction. The prediction of pile-bearing capacity is strongly influenced by ram weight (having a considerable multicollinearity level), and the effect of the considerable multicollinearity level has been determined for the model based on the recurrent neural network approach. In this study, the recurrent neural network model has the least performance and accuracy in predicting the pile-bearing capacity.

With the three dimensional (3D) oblique incident waves exactly determined for the free field, the soil seismic responses in both frequency and time domains are studied by the 2.5 dimension (2.5D) finite/infinite element method. First, the free-field responses in frequency domain are solved exactly for 3D arbitrary incident P and SV waves, which requires no coordinate conversion or extra effort for SV waves with super-critical incident angles. Next, the earthquake spectra are incorporated by the concept of equivalent seismic forces on the near-field boundary, based only on the displacements input derived for unit ground accelerations of each frequency using the 2.5D approach. For the asymmetric 2.5D finite/infinite element model adopted, the procedure for soil seismic analysis is presented. The solutions computed by the proposed method are verified against those of Wolf’s and de Barros and Luco’s and for inversely calculated ground motions. Of interest is that abrupt variation in soil response occurs around the critical angle on the wave propagation plane for SV waves. In addition, the horizontal displacements attenuate with increasing horizontal incident angle, while the longitudinal ones increase inversely for 3D incident P and SV waves.

Time-dependent characteristics (TDCs) have been neglected in most previous studies investigating the deviation mechanisms of bridge pile foundations and evaluating the effectiveness of preventive measures. In this study, the stress-strain-time characteristics of soft soils were illustrated by consolidation-creep tests based on a typical engineering case. An extended Koppejan model was developed and then embedded in a finite element (FE) model via a user-material subroutine (UMAT). Based on the validated FE model, the time-dependent deformation mechanism of the pile foundation was revealed, and the preventive effect of applying micropiles and stress-release holes to control the deviation was investigated. The results show that the calculated maximum lateral displacement of the cap differs from the measured one by 6.5%, indicating that the derived extended Koppejan model reproduced the deviation process of the bridge cap-pile foundation with time. The additional load acting on the pile side caused by soil lateral deformation was mainly concentrated within the soft soil layer and increased with the increase in load duration. Compared with t = 3 d (where t is surcharge time), the maximum lateral additional pressure acting on Pile 2# increased by approximately 47.0% at t = 224 d. For bridge pile foundation deviation in deep soft soils, stress-release holes can provide better prevention compared to micropiles and are therefore recommended.

Reinforced concrete (RC) flat slabs, a popular choice in construction due to their flexibility, are susceptible to sudden and brittle punching shear failure. Existing design methods often exhibit significant bias and variability. Accurate estimation of punching shear strength in RC flat slabs is crucial for effective concrete structure design and management. This study introduces a novel computation method, the jellyfish-least square support vector machine (JS-LSSVR) hybrid model, to predict punching shear strength. By combining machine learning (LSSVR) with jellyfish swarm (JS) intelligence, this hybrid model ensures precise and reliable predictions. The model’s development utilizes a real-world experimental data set. Comparison with seven established optimizers, including artificial bee colony (ABC), differential evolution (DE), genetic algorithm (GA), and others, as well as existing machine learning (ML)-based models and design codes, validates the superiority of the JS-LSSVR hybrid model. This innovative approach significantly enhances prediction accuracy, providing valuable support for civil engineers in estimating RC flat slab punching shear strength.

This study evaluated the feasibility of using polypropylene fiber (PF) as reinforcement in improving tensile strength behavior of cement-stabilized dredged sediment (CDS). The effects of cement content, water content, PF content and length on the tensile strength and stress–strain behavioral evolutions were evaluated by conducting splitting tensile strength tests. Furthermore, the micro-mechanisms characterizing the tensile strength behavior inside PF-reinforced CDS (CPFDS) were clarified via analyzing macro failure and microstructure images. The results indicate that the highest tensile strengths of 7, 28, 60, and 90 d CPFDS were reached at PF contents of 0.6%, 1.0%, 1.0%, and 1.0%, exhibiting values 5.96%, 65.16%, 34.10%, and 35.83% higher than those of CDS, respectively. Short, 3 mm, PF of showed the best reinforcement efficiency. The CPFDS exhibited obvious tensile strain-hardening characteristic, and also had better ductility than CDS. The mix factor (C_C^a/C_w^b) and time parameter (q_t0(t)) of CDS, and the reinforcement index (k_t-PF) of CPFDS were used to establish the tensile strength prediction models of CDS and CPFDS, considering multiple factors. The PF “bridge effect” and associated cementation-reinforcement coupling actions inside CPFDS were mainly responsible for tensile strength behavior improvement. The key findings contribute to the use of CPFDS as recycled engineering soils.

To completely solve the problem of fatigue cracking issue of orthotropic steel bridge decks (OSDs), the authors proposed a steel–ultra-high performance concrete (UHPC) lightweight composite deck (LWCD) with closed ribs in 2010. Based on the successful application of that LWCD, an adaptation incorporating an innovative composite deck structure, i.e., the hot-rolled section steel–UHPC composite deck with open ribs (SSD) is proposed in this paper, aiming to simplify the fabrication process as well as to reduce the cost of LWCD. Based on a long-span cable-stayed bridge, a design scheme is proposed and is compared with the conventional OSD scheme. Further, a finite element (FE) calculation is conducted to reflect both the global and local behavior of the SSD scheme, and it is found that the peaked stresses in the SSD components are less than the corresponding allowable values. A static test is performed for an SSD strip specimen to understand the anti-cracking behavior of the UHPC layer under negative bending moments. The static test results indicate that the UHPC layer exhibited a satisfactory tensile toughness, the UHPC tensile strength obtained from the test is 1.8 times the calculated stress by the FE model of the real bridge. In addition, the fatigue stresses of typical fatigue-prone details in the SSD are calculated and evaluated, and the influences of key design parameters on the fatigue performance of the SSD are analyzed. According to the fatigue results, the peaked stress ranges for all of the 10 fatigue-prone details are within the corresponding constant amplitude fatigue limits. Then a fatigue test is carried out for another SSD strip specimen to explore the fatigue behavior of the fillet weld between the longitudinal and transverse ribs. The specimen failed at the fillet weld after equivalent 47.5 million cycles of loading under the design fatigue stress range, indicating that the fatigue performance of the SSD could meet the fatigue design requirement. Theoretical calculations and experiments provide a basis for the promotion and application of this structure in bridge engineering.

Shield tunnel lining is prone to water leakage, which may further bring about corrosion and structural damage to the walls, potentially leading to dangerous accidents. To avoid tedious and inefficient manual inspection, many projects use artificial intelligence (AI) to detect cracks and water leakage. A novel method for water leakage inspection in shield tunnel lining that utilizes deep learning is introduced in this paper. Our proposal includes a ConvNeXt-S backbone, deconvolutional-feature pyramid network (D-FPN), spatial attention module (SPAM). and a detection head. It can extract representative features of leaking areas to aid inspection processes. To further improve the model’s robustness, we innovatively use an inversed low-light enhancement method to convert normally illuminated images to low light ones and introduce them into the training samples. Validation experiments are performed, achieving the average precision (AP) score of 56.8%, which outperforms previous work by a margin of 5.7%. Visualization illustrations also support our method’s practical effectiveness.

Three-dimensional concrete printing (3DCP) technology begins to be adopted into construction application worldwide. Recent studies have focused on producing a higher concrete quality and offering a user-friendly construction process. Still, the 3DCP construction cost is unlikely to be lower than that of conventional construction, which is especially important for projects where the cost is sensitive. To broaden the 3DCP construction applications, reduction of the quantity of 3DCP material usage is needed. This work aims to perform structural analysis of several patterns of geometric textured 3DCP shell wall structures. 21 different cantilevered textured patterns of 3DCP shell wall structures were architecturally designed and then subjected to structural analysis by a finite element method (FEM). The results indicated that by designing appropriate patterns, the structural performance to weight ratio could be improved up to 300%. The study therefore offers an innovative design process for constructing 3DCP housing and suggests pre-construction analysis methods for 3DCP shell wall structures.

The thixotropic structural build-up is crucial in extrusion-based three-dimensional (3D) concrete printing. This paper uses a theoretical model to predict the evolution of static and dynamic yield stress for printed concrete. The model employs a structural kinetics framework to create a time-independent constitutive link between shear stress and shear rate. The model considers flocculation, deflocculation, and chemical hydration to anticipate structural buildability. The reversible and irreversible contributions that occur throughout the build-up, breakdown, and hydration are defined based on the proposed structural parameters. Additionally, detailed parametric studies are conducted to evaluate the impact of model parameters. It is revealed that the proposed model is in good agreement with the experimental results, and it effectively characterizes the structural build-up of 3D printable concrete.

The importance of geometrical control of three dimensional (3D) printable concrete without the support of formwork is widely acknowledged. In this study, a numerical model based on computational fluid dynamics was developed to evaluate the geometrical quality of a 3D printed layer. The numerical results were compared, using image analysis, with physical cross-sectional sawn samples. The influence of printing parameters (printing speed, nozzle height, and nozzle diameter) and the rheological behavior of printed materials (yield stress), on the geometrical quality of one printed layer was investigated. In addition, the yield zone of the printed layer was analyzed, giving insights on the critical factors for geometrical control in 3D concrete printing. Results indicated that the developed model can precisely describe the extrusion process, as well as the cross-sectional quality.

The hazardous environmental effects of greenhouse gas emissions and climate change demand alternative sources for cementitious materials in the construction industry. The development of geopolymer structures provides a way of producing 100% cement-free construction. In this research work, a novel and simple way of deriving nano particles from waste fly ash particles is promoted. The effect of adding the synthesized nano fly ash particles as a filler medium in geopolymer mortars was investigated by considering strength and durability properties. Parameter optimization was done by using regression analysis on the geopolymer mortar and the impact of adding nano fly ash particles was studied by varying different percentages of addition ranging from 0 to 7.5% by weight of binder content. From the results, it was observed that 1% nano fly ash acted not only as a filler but also as nano-sized precursors of the polymerization process, resulting in denser geopolymer medium. This can explain the extraordinary gain in strength of 72.11 MPa as well as the denser core with negligible level of chloride ion penetration, making the material suitable for the development of structures susceptible to marine environment.

This study discusses the effects of local sites and hazard amplification on the seismic vulnerability assessment of existing masonry buildings. In this context, a rapid seismic evaluation procedure was implemented on an old masonry building stock in the historical center Galata, located in İstanbul, to determine the seismic risk priority of the built heritage. Damage scenarios were generated for all soil classes, different moment magnitudes, and source-to-site distances to obtain more accurate results for the seismic vulnerability assessment of the studied building stock. Consequently, damage distributions estimated under nine different scenarios with/without site effects were compared and illustrated in maps to discuss changes in vulnerability owing to amplification effects. In this study, by re-examining the rapid seismic evaluation procedure by including geo-hazard-based assessment, the importance of site effects on the vulnerability and risk assessment of built heritage was underlined. The proposed framework integrating field data and local site effects is believed to advance the current applications for vulnerability assessment of masonry buildings and provide an improvement in the application of rapid seismic assessment procedures with more reliable results.

Face passive failure can severely damage existing structures and underground utilities during shallow shield tunneling, especially in coastal backfill sand. In this work, a series of laboratory model tests were developed and conducted to investigate such failure, for tunnels located at burial depth ratios for which C/D = 0.5, 0.8, 1, and 1.3. Support pressures, the evolution of failure processes, the failure modes, and the distribution of velocity fields were examined through model tests and numerical analyses. The support pressure in the tests first rose rapidly to the elastic limit and then gradually increased to the maximum value in all cases. The maximum support pressure decreased slightly in cases where C/D = 0.8, 1, and 1.3, but the rebound was insignificant where C/D = 0.5. In addition, the configuration of the failure mode with C/D = 0.5 showed a wedge-shaped arch, which was determined by the outcropping shear failure. The configuration of failure modes was composed of an arch and the inverted trapezoid when C/D = 0.8, 1, and 1.3, in which the mode was divided into lower and upper failure zones.

This work uses isogeometric analysis (IGA), which is based on nonlocal hypothesis and higher-order shear beam hypothesis, to investigate the static bending and free oscillation of a magneto-electro-elastic functionally graded (MEE-FG) nanobeam subject to elastic boundary constraints (BCs). The magneto-electric boundary condition and the Maxwell equation are used to calculate the variation of electric and magnetic potentials along the thickness direction of the nanobeam. This study is innovative since it does not use the conventional boundary conditions. Rather, an elastic system of straight and torsion springs with controllable stiffness is used to support nanobeams’ beginning and end positions, creating customizable BCs. The governing equations of motion of nanobeams are established by applying Hamilton’s principle and IGA is used to determine deflections and natural frequency values. Verification studies were performed to evaluate the convergence and accuracy of the proposed method. Aside from this, the impact of the input parameters on the static bending and free oscillation of the MEE-FG nanobeam is examined in detail. These findings could be valuable for analyzing and designing innovative structures constructed of functionally graded MEE materials.

The derivation and validation of analytical equations for predicting the tensile initial stiffness of thread-fixed one-side bolts (TOBs), connected to enclosed rectangular hollow section (RHS) columns, is presented in this paper. Two unknown stiffness components are considered: the TOBs connection and the enclosed RHS face. First, the trapezoidal thread of TOB, as an equivalent cantilevered beam subjected to uniformly distributed loads, is analyzed to determine the associated deformations. Based on the findings, the thread-shank serial-parallel stiffness model of TOB connection is proposed. For analysis of the tensile stiffness of the enclosed RHS face due to two bolt forces, the four sidewalls are treated as rotation constraints, thus reducing the problem to a two-dimensional plate analysis. According to the load superposition method, the deflection of the face plate is resolved into three components under various boundary and load conditions. Referring to the plate deflection theory of Timoshenko, the analytical solutions for the three deflections are derived in terms of the variables of bolt spacing, RHS thickness, height to width ratio, etc. Finally, the validity of the above stiffness equations is verified by a series of finite element (FE) models of T-stub substructures. The proposed component stiffness equations are an effective supplement to the component-based method.

The recycled powder (RP) from construction wastes can be used to partially replace cement in the preparation of reactive powder concrete. In this paper, reactive powder concrete mixtures with RP partially replacing cement, and natural sand instead of quartz, are developed. Standard curing is used, instead of steam curing that is normally requested by standard for reactive powder concrete. The influences of RP replacement ratio (0, 10%, 20%, 30%), silica fume proportion (10%, 15%, 20%), and steel fiber proportion (0, 1%, 2%) are investigated. The effects of RP, silica fume, and steel fiber proportion on compressive strength, elastic modulus, and relative absorption energy are analyzed, and theoretical models for compressive strength, elastic modulus, and relative absorption energy are established. A constitutive model for the uniaxial compressive stress–strain relationship of reactive powder concrete with RP is developed. With the increase of RP replacement ratio from 0% to 30%, the compressive strength decreases by 42% and elastic modulus decreases by 24%.

The use of prefabricated vertical drains (PVD) in liquefiable deposits is gaining attention due to enhanced drainage. However, investigations on PVD in mitigating re-liquefaction during repeated shaking events are not available. This study performed a series of shaking table experiments on untreated and PVD-treated specimens prepared with 40% and 60% relative density. Repeated sinusoidal loading was applied with an incremental peak acceleration of 0.1g, 0.2g, 0.3g, and 0.4g, at 5 Hz shaking frequency with 40 s duration. The performance of treated ground was evaluated based on the generation and dissipation of excess pore water pressure (EPWP), induced sand densification, subsidence, and cyclic stress ratio. In addition, the strain accumulated in fresh and exhumed PVD was investigated using geotextile tensile testing apparatus aided with digital image correlation. No evidence of pore pressure was reported up to 0.2g peak acceleration for 40% and 60% relative density specimens. The continuous occurrence of soil densification and drainage medium restrained and delayed the generation of EPWP and expedited the dissipation process. This study demonstrates PVD can mitigate re-liquefaction, without suffering from deterioration, when subjected to medium to high intense repeated shaking events.

Researchers are paying increasing attention to the development of low-cost and microcontroller-based accelerometers, in order to make structural health monitoring feasible for conventional bridges with limited monitoring budget. Parallel with the low-cost sensor development, the use of the embedded accelerometers of smartphones for eigenfrequency analysis of bridges is becoming popular in the civil engineering literature. This paper, for the first time in the literature, studies these two promising technologies by comparing the noise density and eigenfrequency analysis of a self-developed, validated and calibrated low-cost Internet of things based accelerometer LARA (low cost adaptable reliable accelerometer) with those of a state of the art smartphone (iPhone XR). The eigenfrequency analysis of a footbridge in San Sebastian, Spain, showed that the embedded accelerometer of the iPhone XR can measure the natural frequencies of the under study bridge.

The brittleness of cement composites makes cracks almost inevitable, producing a serious limitation on the lifespan, resilience, and safety of concrete infrastructure. To address this brittleness, self-healing concrete has been developed for regaining its mechanical and durability properties after becoming cracked, thereby promising sustainable development of concrete infrastructure. This paper provides a comprehensive review of the latest developments in self-healing concrete. It begins by summarizing the methods used to evaluate the self-healing efficiency of concrete. Next, it compares strategies for achieving healing concrete. It then discusses the typical approaches for developing self-healing concrete. Finally, critical insights are proposed to guide future studies on the development of novel self-healing concrete. This review will be useful for researchers and practitioners interested in the field of self-healing concrete and its potential to improve the durability, resilience, and safety of concrete infrastructure.